Handheld electronic device with text disambiguation employing advanced text case feature

ABSTRACT

A handheld electronic device includes a reduced QWERTY keyboard and is enabled with disambiguation software. The device provides an improved text case feature. The device provides output in the form of a default output and a number of variants. The output is based largely upon the frequency, i.e., the likelihood that a user intended a particular output, but various features of the device provide additional variants that are not based solely on frequency and rather are provided by various logic structures resident on the device. The device enables editing during text entry and also provides a learning function that allows the disambiguation function to adapt to provide a customized experience for the user. The disambiguation function can be selectively disabled and an alternate keystroke interpretation system provided. Additionally, the device can facilitate the selection of variants by displaying a graphic of a special &lt;NEXT&gt; key of the keypad that enables a user to progressively select variants generally without changing the position of the user&#39;s hands on the device. If a field into which text is being entered is determined to be a special input field, a disambiguated result can be sought first from a predetermined data source prior to seeking results from other data sources on the device.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention relates generally to handheld electronic devices and, moreparticularly, to a handheld electronic device having a reduced keyboardand an input disambiguation function, and also relates to an associatedmethod.

2. Background Information

Numerous types of handheld electronic devices are known. Examples ofsuch handheld electronic devices include, for instance, personal dataassistants (PDAs), handheld computers, two-way pagers, cellulartelephones, and the like. Many handheld electronic devices also featurewireless communication capability, although many such handheldelectronic devices are stand-alone devices that are functional withoutcommunication with other devices.

Such handheld electronic devices are generally intended to be portable,and thus are of a relatively compact configuration in which keys andother input structures often perform multiple functions under certaincircumstances or may otherwise have multiple aspects or featuresassigned thereto. With advances in technology, handheld electronicdevices are built to have progressively smaller form factors yet haveprogressively greater numbers of applications and features residentthereon. As a practical matter, the keys of a keypad can only be reducedto a certain small size before the keys become relatively unusable. Inorder to enable text entry, however, a keypad must be capable ofentering all twenty-six letters of the Latin alphabet, for instance, aswell as appropriate punctuation and other symbols.

One way of providing numerous letters in a small space has been toprovide a “reduced keyboard” in which multiple letters, symbols, and/ordigits, and the like, are assigned to any given key. For example, atouch-tone telephone includes a reduced keypad by providing twelve keys,of which ten have digits thereon, and of these ten keys eight have Latinletters assigned thereto. For instance, one of the keys includes thedigit “2” as well as the letters “A”, “B”, and “C”. Other known reducedkeyboards have included other arrangements of keys, letters, symbols,digits, and the like. Since a single actuation of such a key potentiallycould be intended by the user to refer to any of the letters “A”, “B”,and “C”, and potentially could also be intended to refer to the digit“2”, the input generally is an ambiguous input and is in need of sometype of disambiguation in order to be useful for text entry purposes.

In order to enable a user to make use of the multiple letters, digits,and the like on any given key, numerous keystroke interpretation systemshave been provided. For instance, a “multi-tap” system allows a user tosubstantially unambiguously specify a particular linguistic element on akey by pressing the same key a number of times equivalent to theposition of the desired linguistic element on the key. For example, onthe aforementioned telephone key that includes the letters “ABC”, andthe user desires to specify the letter “C”, the user will press the keythree times. While such multi-tap systems have been generally effectivefor their intended purposes, they nevertheless can require a relativelylarge number of key inputs compared with the number of linguisticelements that ultimately are output.

Another exemplary keystroke interpretation system would include keychording, of which various types exist. For instance, a particularlinguistic element can be entered by pressing two keys in succession orby pressing and holding first key while pressing a second key. Stillanother exemplary keystroke interpretation system would be a“press-and-hold/press-and-release” interpretation function in which agiven key provides a first result if the key is pressed and immediatelyreleased, and provides a second result if the key is pressed and heldfor a short period of time. While they systems have likewise beengenerally effective for their intended purposes, such systems also havetheir own unique drawbacks.

Another keystroke interpretation system that has been employed is asoftware-based text disambiguation function. In such a system, a usertypically presses keys to which one or more linguistic elements havebeen assigned, generally pressing each key one time for each desiredletter, and the disambiguation software attempt to predict the intendedinput. Numerous such systems have been proposed, and while many havebeen generally effective for their intended purposes, shortcomings stillexist.

It would be desirable to provide an improved handheld electronic devicewith a reduced keyboard that seeks to mimic a QWERTY keyboard experienceor other particular keyboard experience. Such an improved handheldelectronic device might also desirably be configured with enoughfeatures to enable text entry and other tasks with relative ease.

SUMMARY OF THE INVENTION

In view of the foregoing, an improved handheld electronic deviceincludes a keypad in the form of a reduced QWERTY keyboard and isenabled with disambiguation software. The device provides an improvedtext case feature. As a user enters keystrokes, the device providesoutput in the form of a default output and a number of variants fromwhich a user can choose. The output is based largely upon the frequency,i.e., the likelihood that a user intended a particular output, butvarious features of the device provide additional variants that are notbased solely on frequency and rather are provided by various logicstructures resident on the device. The device enables editing duringtext entry and also provides a learning function that allows thedisambiguation function to adapt to provide a customized experience forthe user. In certain predefined circumstances, the disambiguationfunction can be selectively disabled and an alternate keystrokeinterpretation system provided. Additionally, the device can facilitatethe selection of variants by displaying a graphic of a special <NEXT>key of the keypad that enables a user to progressively select variantsgenerally without changing the position of the user's hands on thedevice. If a field into which text is being entered is determined to bea special input field, a disambiguated result can be sought first from apredetermined data source prior to seeking results from other datasources on the device.

Accordingly, an aspect of the invention is to provide an improvedhandheld electronic device and an associated method, with the handheldelectronic device including a reduced keyboard that seeks to simulate aQWERTY keyboard experience or another particular keyboard experience.

Another aspect of the invention is to provide an improved handheldelectronic devices and an associated method that provide a text inputdisambiguation function.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that employ a disambiguationfunction that, responsive to an ambiguous input, provides a number ofproposed outputs according to relative frequency.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that provide a number ofproposed outputs that can be based upon relative frequency and/or canresult from various logic structures resident on the device.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that enable a customexperience by a user based upon various learning features and otherfeatures.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that employ a disambiguationfunction that can be selectively disabled in certain predefinedcircumstances.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method, wherein the handheldelectronic device includes an input apparatus which facilitates theselection of variants with relative ease.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that employ a disambiguationfunction to disambiguate text input from a reduced QWERTY keyboard orother keyboard and that allow editing of the text input.

Another aspect of the invention is to provide an improved handheldelectronic device and an associated method that employ a disambiguationfunction to disambiguate text input in a fashion that can searchpredetermined data sources for disambiguation data prior to searchingother data sources if the input field is determined to be a specialinput field.

Accordingly, an aspect of the invention is to provide an improved methodof disambiguating an input into a handheld electronic device. Thehandheld electronic device includes an input apparatus, an outputapparatus, and a processor apparatus including a memory having aplurality of objects stored therein. The plurality of objects include aplurality of language objects, with each language object of at least aportion of the plurality of language objects comprising at least a firstlinguistic element. The input apparatus includes a plurality of inputmembers, with each of at least a portion of the input members of theplurality of input members having a plurality of linguistic elementsassigned thereto. The general nature of the method can be stated asincluding detecting an ambiguous input including a number of inputmember actuations of a number of the input members of the plurality ofinput members, with each of at least a portion of the input members ofthe number of input members including a number of linguistic elementsassigned thereto, and with at least one of the input members of thenumber of input members having a plurality of linguistic elementsassigned thereto. The method further includes generating a number ofprefix objects corresponding with the ambiguous input, with each prefixobject of the number of prefix objects including a number of thelinguistic elements of the number of the input members of the ambiguousinput. The method also includes, for at least a first prefix object ofthe number of prefix objects, identifying at least a pair of languageobjects of the plurality of language objects corresponding with the atleast a first prefix object, with at least a portion of a first languageobject of the at least a pair of language objects having a first casemakeup comprising a number of case elements, with at least a portion ofa second language object of the at least a pair of language objectshaving a second case makeup comprising a number of case elements, andwith the first case makeup and the second case makeup being differentthan one another. The method also includes outputting the at least afirst prefix object in accordance with the first case makeup andoutputting the at least a first prefix object in accordance with thesecond case makeup.

Another aspect of the invention is to provide an improved method ofdisambiguating an input into a handheld electronic device. The handheldelectronic device includes an input apparatus, an output apparatus, anda processor apparatus including a memory having a plurality of objectsstored therein. The plurality of objects include a plurality of languageobjects. Each language object of at least a portion of the plurality oflanguage objects comprises at least a first linguistic element. Theinput apparatus includes a plurality of input members, with each of atleast a portion of the input members of the plurality of input membershaving a plurality of linguistic elements assigned thereto. The generalnature of the method can be stated as including detecting an ambiguousinput including a number of input member actuations of a number of theinput members of the plurality of input members, with each of at least aportion of the input members of the number of input members including anumber of linguistic elements assigned thereto, with at least one of theinput members of the number of input members having a plurality oflinguistic elements assigned thereto, and with the ambiguous inputhaving an input case makeup comprising a number of case elements. Themethod also includes generating a number of prefix objects correspondingwith the ambiguous input, with each prefix object of the number ofprefix objects including a number of the linguistic elements of thenumber of the input members of the ambiguous input. The method alsoincludes, for at least a first prefix object of the number of prefixobjects, identifying at least a pair of language objects of theplurality of language objects corresponding with the at least a firstprefix object, with at least a portion of a first language object of theat least a pair of language objects having a first case makeupcomprising a number of case elements, with at least a portion of asecond language object of the at least a pair of language objects havinga second case makeup comprising a number of case elements, and with thefirst case makeup and the second case makeup being different than oneanother. The method further includes determining that at least a portionof the input case makeup including a case element that is upper casecorresponds with at least a portion of one of the first case makeup andthe second case makeup, and outputting the at least a first prefixobject in accordance with the one of the first case makeup and thesecond case makeup.

Another aspect of the invention is to provide an improved method ofdisambiguating an input into a handheld electronic device. The handheldelectronic device includes an input apparatus, an output apparatus, anda processor apparatus including a memory having a plurality of objectsstored therein, with the plurality of objects including a plurality oflanguage objects. Each language object of at least a portion of theplurality of language objects comprises at least a first linguisticelement. The input apparatus includes a plurality of input members, witheach of at least a portion of the input members of the plurality ofinput members having a plurality of linguistic elements assignedthereto. The general nature of the method can be stated as includingdetecting an ambiguous input including a number of input memberactuations of a number of the input members of the plurality of inputmembers, with each of at least a portion of the input members of thenumber of input members including a number of linguistic elementsassigned thereto, and with at least one of the input members of thenumber of input members having a plurality of linguistic elementsassigned thereto. The method further includes generating a number ofprefix objects corresponding with the ambiguous input, with each prefixobject of the number of prefix objects including a number of thelinguistic elements of the number of the input members of the ambiguousinput, and with the ambiguous input having an input case makeupcomprising a number of case elements. The method further includes, for aprefix object of the number of prefix objects, identifying a languageobject of the plurality of language objects that corresponds therewith,with at least a portion of the identified language object having astored case makeup comprising a number of case elements, and with atleast a portion of the input case makeup and at least a portion of thestored case makeup being different than one another. The method furtherincludes outputting as a variant the prefix object in accordance withthe stored case makeup.

BRIEF DESCRIPTION OF THE DRAWINGS

A full understanding of the invention can be gained from the followingDescription of the Preferred Embodiment when read in conjunction withthe accompanying drawings in which:

FIG. 1 is a top plan view of an improved handheld electronic device inaccordance with the invention;

FIG. 2 is a schematic depiction of the improved handheld electronicdevice of FIG. 1;

FIG. 2 a is a schematic depiction of a portion of the handheldelectronic device of FIG. 2;

FIGS. 3 a and 3 b are an exemplary flowchart depicting certain aspectsof a disambiguation function that can be executed on the handheldelectronic device of FIG. 1;

FIG. 4 is another exemplary flowchart depicting certain aspects of adisambiguation function that can be executed on the handheld electronicdevice by which certain output variants can be provided to the user;

FIGS. 5 a and 5 b are another exemplary flowchart depicting certainaspects of the learning method that can be executed on the handheldelectronic device;

FIG. 6 is another exemplary flowchart depicting certain aspects of amethod by which various display formats that can be provided on thehandheld electronic device;

FIG. 6A are another exemplary flowchart depicting certain aspects of themethod that can be executed on the handheld electronic device;

FIG. 7 is an exemplary output during a text entry operation;

FIG. 8 is another exemplary output during another part of the text entryoperation;

FIG. 9 is another exemplary output during another part of the text entryoperation;

FIG. 10 is another exemplary output during another part of the textentry operation;

FIG. 11 is an exemplary output on the handheld electronic device duringanother text entry operation;

FIG. 12 is an exemplary output that can be provided in an instance whenthe disambiguation function of the handheld electronic device has beendisabled.

FIG. 13 is an exemplary output during a part of another text entryoperation;

FIG. 14 is another exemplary output during another part of the textentry operation;

FIG. 15 is another exemplary output during another part of the textentry operation;

FIG. 16 is another exemplary output during another part of the textentry operation;

FIG. 17 is another exemplary output during another part of the textentry operation;

FIG. 18 is an exemplary output during a part of another text entryoperation;

FIG. 19 is another exemplary output during another part of the textentry operation;

FIG. 20 is another exemplary output during another part of the textentry operation;

FIG. 21 is another exemplary output during another part of the textentry operation;

FIG. 22 is an exemplary output during a part of another text entryoperation; and

FIG. 23 is another exemplary output during another part of the textentry operation.

Similar numerals refer to similar parts throughout the specification.

DESCRIPTION OF THE PREFERRED EMBODIMENT

An improved handheld electronic device 4 is indicated generally in FIG.1 and is depicted schematically in FIG. 2. The exemplary handheldelectronic device 4 includes a housing 6 upon which are disposed aprocessor unit that includes an input apparatus 8, an output apparatus12, a processor 16, a memory 20, and at least a first routine. Theprocessor 16 may be, for instance, and without limitation, amicroprocessor (μP) and is responsive to inputs from the input apparatus8 and provides output signals to the output apparatus 12. The processor16 also interfaces with the memory 20. Examples of handheld electronicdevices are included in U.S. Pat. Nos. 6,452,588 and 6,489,950, whichare incorporated by record herein.

As can be understood from FIG. 1, the input apparatus 8 includes akeypad 24 and a thumbwheel 32. As will be described in greater detailbelow, the keypad 24 is in the exemplary form of a reduced QWERTYkeyboard including a plurality of keys 28 that serve as input members.It is noted, however, that the keypad 24 may be of other configurations,such as an AZERTY keyboard, a QWERTZ keyboard, or other keyboardarrangement, whether presently known or unknown, and either reduced ornot reduced. As employed herein, the expression “reduced” and variationsthereof in the context of a keyboard, a keypad, or other arrangement ofinput members, shall refer broadly to an arrangement in which at leastone of the input members has assigned thereto a plurality of linguisticelements such as, for example, linguistic elements in the set of Latinletters, whereby an actuation of the at least one of the input members,without another input in combination therewith, is an ambiguous inputsince it could refer to more than one of the plurality of linguisticelements assigned thereto. As employed herein, the expression“linguistic element” and variations thereof shall refer broadly to anyelement that itself can be a language object or from which a languageobject can be constructed, identified, or otherwise obtained, and thuswould include, for example and without limitation, linguistic elements,letters, strokes, ideograms, phonemes, morphemes, digits, and the like.As employed herein, the expression “language object” and variationsthereof shall refer broadly to any type of object that may beconstructed, identified, or otherwise obtained from one or morelinguistic elements, that can be used alone or in combination togenerate text, and that would include, for example and withoutlimitation, words, shortcuts, symbols, ideograms, and the like.

The system architecture of the handheld electronic device 4advantageously is organized to be operable independent of the specificlayout of the keypad 24. Accordingly, the system architecture of thehandheld electronic device 4 can be employed in conjunction withvirtually any keypad layout substantially without requiring anymeaningful change in the system architecture. It is further noted thatcertain of the features set forth herein are usable on either or both ofa reduced keyboard and a non-reduced keyboard.

The keys 28 are disposed on a front face of the housing 6, and thethumbwheel 32 is disposed at a side of the housing 6. The thumbwheel 34can serve as another input member and is both rotatable, as is indicatedby the arrow 34, to provide selection inputs to the processor 16, andalso can be pressed in a direction generally toward the housing 6, as isindicated by the arrow 38, to provide another selection input to theprocessor 16.

Among the keys 28 of the keypad 24 are a <NEXT> key 40 and an <ENTER>key 44. The <NEXT> key 40 can be pressed to provide a selection input tothe processor 16 and provides substantially the same selection input asis provided by a rotational input of the thumbwheel 32. Since the <NEXT>key 40 is provided adjacent a number of the other keys 28 of the keypad24, the user can provide a selection input to the processor 16substantially without moving the user's hands away from the keypad 24during a text entry operation. As will be described in greater detailbelow, the <NEXT> key 40 additionally and advantageously includes agraphic 42 disposed thereon, and in certain circumstances the outputapparatus 12 also displays a displayed graphic 46 thereon to identifythe <NEXT> key 40 as being able to provide a selection input to theprocessor 16. In this regard, the displayed graphic 46 of the outputapparatus 12 is substantially similar to the graphic 42 on the <NEXT>key and thus identifies the <NEXT> key 40 as being capable of providinga desirable selection input to the processor 16.

As can further be seen in FIG. 1, many of the keys 28 include a numberof linguistic elements 48 disposed thereon. As employed herein, theexpression “a number of” and variations thereof shall refer broadly toany quantity, including a quantity of one, and in certain circumstancesherein can also refer to a quantity of zero. In the exemplary depictionof the keypad 24, many of the keys 28 include two linguistic elements,such as including a first linguistic element 52 and a second linguisticelement 56 assigned thereto.

One of the keys 28 of the keypad 24 includes as the linguistic elements48 thereof the letters “Q” and “W”, and an adjacent key 28 includes asthe linguistic elements 48 thereof the letters “E” and “R”. It can beseen that the arrangement of the linguistic elements 48 on the keys 28of the keypad 24 is generally of a QWERTY arrangement, albeit with manyof the keys 28 including two of the linguistic elements 28.

The output apparatus 12 includes a display 60 upon which can be providedan output 64. An exemplary output 64 is depicted on the display 60 inFIG. 1. The output 64 includes a text component 68 and a variantcomponent 72. The variant component 72 includes a default portion 76 anda variant portion 80. The display also includes a caret 84 that depictsgenerally where the next input from the input apparatus 8 will bereceived.

The text component 68 of the output 64 provides a depiction of thedefault portion 76 of the output 64 at a location on the display 60where the text is being input. The variant component 72 is disposedgenerally in the vicinity of the text component 68 and provides, inaddition to the default proposed output 76, a depiction of the variousalternate text choices, i.e., alternates to the default proposed output76, that are proposed by an input disambiguation function in response toan input sequence of key actuations of the keys 28.

As will be described in greater detail below, the default portion 76 isproposed by the disambiguation function as being the most likelydisambiguated interpretation of the ambiguous input provided by theuser. The variant portion 80 includes a predetermined quantity ofalternate proposed interpretations of the same ambiguous input fromwhich the user can select, if desired. The displayed graphic 46typically is provided in the variant component 72 in the vicinity of thevariant portion 80, although it is understood that the displayed graphic46 could be provided in other locations and in other fashions withoutdeparting from the concept of the invention. It is also noted that theexemplary variant portion 80 is depicted herein as extending verticallybelow the default portion 76, but it is understood that numerous otherarrangements could be provided without departing from the concept of theinvention.

Among the keys 28 of the keypad 24 additionally is a <DELETE> key 86that can be provided to delete a text entry. As will be described ingreater detail below, the <DELETE> key 86 can also be employed inproviding an alternation input to the processor 16 for use by thedisambiguation function.

The memory 20 is depicted schematically in FIG. 2A. The memory 20 can beany of a variety of types of internal and/or external storage media suchas, without limitation, RAM, ROM, EPROM(s), EEPROM(s), and the like thatprovide a storage register for data storage such as in the fashion of aninternal storage area of a computer, and can be volatile memory ornonvolatile memory. The memory 20 additionally includes a number ofroutines depicted generally with the numeral 22 for the processing ofdata. The routines 22 can be in any of a variety of forms such as,without limitation, software, firmware, and the like. As will beexplained in greater detail below, the routines 22 include theaforementioned disambiguation function as an application, as well asother routines.

As can be understood from FIG. 2A, the memory 20 additionally includesdata stored and/or organized in a number of tables, sets, lists, and/orotherwise. Specifically, the memory 20 includes a generic word list 88,a new words database 92, and a frequency learning database 96. Storedwithin the various areas of the memory 20 are a number of languageobjects 100 and frequency objects 104. The language objects 100generally are each associated with an associated frequency object 104.The language objects 100 include, in the present exemplary embodiment, aplurality of word objects 108 and a plurality of N-gram objects 112. Theword objects 108 are generally representative of complete words withinthe language or custom words stored in the memory 22. For instance, ifthe language stored in the memory is, for example, English, generallyeach word object 108 would represent a word in the English language orwould represent a custom word.

Associated with substantially each word object 108 is a frequency object104 having frequency value that is indicative of the relative frequencywithin the relevant language of the given word represented by the wordobject 108. In this regard, the generic word list 88 includes a corpusof word objects 108 and associated frequency objects 104 that togetherare representative of a wide variety of words and their relativefrequency within a given vernacular of, for instance, a given language.The generic word list 88 can be derived in any of a wide variety offashions, such as by analyzing numerous texts and other language sourcesto determine the various words within the language sources as well astheir relative probabilities, i.e., relative frequencies, of occurrencesof the various words within the language sources.

The N-gram objects 112 stored within the generic word list 88 are shortstrings of linguistic elements within the relevant language typically,for example, one to three linguistic elements in length, and typicallyrepresent word fragments within the relevant language, although certainof the N-gram objects 112 additionally can themselves be words. However,to the extent that an N-gram object 112 also is a word within therelevant language, the same word likely would be separately stored as aword object 108 within the generic word list 88. As employed herein, theexpression “string” and variations thereof shall refer broadly to anobject having one or more linguistic elements or components, and canrefer to any of a complete word, a fragment of a word, a custom word orexpression, and the like.

In the present exemplary embodiment of the handheld electronic device 4,the N-gram objects 112 include 1-gram objects, i.e., string objects thatare one linguistic element in length, 2-gram objects, i.e., stringobjects that are two linguistic elements in length, and 3-gram objects,i.e., string objects that are three linguistic elements in length, allof which are collectively referred to as N-grams 112. Substantially eachN-gram object 112 in the generic word list 88 is similarly associatedwith an associated frequency object 104 stored within the generic wordlist 88, but the frequency object 104 associated with a given N-gramobject 112 has a frequency value that indicates the relative probabilitythat the linguistic element string represented by the particular N-gramobject 112 exists at any location within any word of the relevantlanguage. The N-gram objects 112 and the associated frequency objects104 are a part of the corpus of the generic word list 88 and areobtained in a fashion similar to the way in which the word object 108and the associated frequency objects 104 are obtained, although theanalysis performed in obtaining the N-gram objects 112 will be slightlydifferent because it will involve analysis of the various linguisticelement strings within the various words instead of relying primarily onthe relative occurrence of a given word.

The present exemplary embodiment of the handheld electronic device 4,with its exemplary language being the English language, includestwenty-six 1-gram N-gram objects 112, i.e., one 1-gram object for eachof the twenty-six letters in the Latin alphabet upon which the Englishlanguage is based, and further includes 676 2-gram N-gram objects 112,i.e., twenty-six squared, representing each two-letter permutation ofthe twenty-six letters within the Latin alphabet.

The N-gram objects 112 also include a certain quantity of 3-gram N-gramobjects 112, primarily those that have a relatively high frequencywithin the relevant language. The exemplary embodiment of the handheldelectronic device 4 includes fewer than all of the three-letterpermutations of the twenty-six letters of the Latin alphabet due toconsiderations of data storage size, and also because the 2-gram N-gramobjects 112 can already provide a meaningful amount of informationregarding the relevant language. As will be set forth in greater detailbelow, the N-gram objects 112 and their associated frequency objects 104provide frequency data that can be attributed to linguistic elementstrings for which a corresponding word object 108 cannot be identifiedor has not been identified, and typically is employed as a fallback datasource, although this need not be exclusively the case.

In the present exemplary embodiment, the language objects 100 and thefrequency objects 104 are maintained substantially inviolate in thegeneric word list 88, meaning that the basic language corpus remainssubstantially unaltered within the generic word list 88, and thelearning functions that are provided by the handheld electronic device 4and that are described below operate in conjunction with other objectthat are generally stored elsewhere in memory 20, such as, for example,in the new words database 92 and the frequency learning database 96.

The new words database 92 and the frequency learning database 96 storeadditional word objects 108 and associated frequency objects 104 inorder to provide to a user a customized experience in which words andthe like that are used relatively more frequently by a user will beassociated with relatively higher frequency values than might otherwisebe reflected in the generic word list 88. More particularly, the newwords database 92 includes word objects 108 that are user-defined andthat generally are not found among the word objects 108 of the genericword list 88. Each word object 108 in the new words database 92 hasassociated therewith an associated frequency object 104 that is alsostored in the new words database 92. The frequency learning database 96stores word objects 108 and associated frequency objects 104 that areindicative of relatively more frequent usage of such words by a userthan would be reflected in the generic word list 88. As such, the newwords database 92 and the frequency learning database 96 provide twolearning functions, that is, they together provide the ability to learnnew words as well the ability to learn altered frequency values forknown words.

FIGS. 3 a and 3 b depicts in an exemplary fashion the general operationof certain aspects of the disambiguation function of the handheldelectronic device 4. Additional features, functions, and the like aredepicted and described elsewhere.

An input is detected, as at 204, and the input can be any type ofactuation or other operation as to any portion of the input apparatus 8.A typical input would include, for instance, an actuation of a key 28having a number of linguistic elements 48 thereon, or any other type ofactuation or manipulation of the input apparatus 8.

Upon detection at 204 of an input, a timer is reset at 208. The use ofthe timer will be described in greater detail below.

The disambiguation function then determines, as at 212, whether thecurrent input is an operational input, such as a selection input, adelimiter input, a movement input, an alternation input, or, forinstance, any other input that does not constitute an actuation of a key28 having a number of linguistic elements 48 thereon. If the input isdetermined at 212 to not be an operational input, processing continuesat 216 by adding the input to the current input sequence which may ormay not already include an input.

Many of the inputs detected at 204 are employed in generating inputsequences as to which the disambiguation function will be executed. Aninput sequence is build up in each “session” with each actuation of akey 28 having a number of linguistic elements 48 thereon. Since an inputsequence typically will be made up of at least one actuation of a key 28having a plurality of linguistic elements 48 thereon, the input sequencewill be ambiguous. When a word, for example, is completed the currentsession is ended an a new session is initiated.

An input sequence is gradually built up on the handheld electronicdevice 4 with each successive actuation of a key 28 during any givensession. Specifically, once a delimiter input is detected during anygiven session, the session is terminated and a new session is initiated.Each input resulting from an actuation of one of the keys 28 having anumber of the linguistic elements 48 associated therewith issequentially added to the current input sequence. As the input sequencegrows during a given session, the disambiguation function generally isexecuted with each actuation of a key 28, i.e., and input, and as to theentire input sequence. Stated otherwise, within a given session, thegrowing input sequence is attempted to be disambiguated as a unit by thedisambiguation function with each successive actuation of the variouskeys 28.

Once a current input representing a most recent actuation of the one ofthe keys 28 having a number of the linguistic elements 48 assignedthereto has been added to the current input sequence within the currentsession, as at 216 in FIG. 3 a, the disambiguation function generates,as at 220, substantially all of the permutations of the linguisticelements 48 assigned to the various keys 28 that were actuated ingenerating the input sequence. In this regard, the “permutations” referto the various strings that can result from the linguistic elements 48of each actuated key 28 limited by the order in which the keys 28 wereactuated. The various permutations of the linguistic elements in theinput sequence are employed as prefix objects.

For instance, if the current input sequence within the current sessionis the ambiguous input of the keys “AS” and “OP”, the variouspermutations of the first linguistic element 52 and the secondlinguistic element 56 of each of the two keys 28, when considered in thesequence in which the keys 28 were actuated, would be “SO”, “SP”, “AP”,and “AO”, and each of these is a prefix object that is generated, as at220, with respect to the current input sequence. As will be explained ingreater detail below, the disambiguation function seeks to identify foreach prefix object one of the word objects 108 for which the prefixobject would be a prefix.

The method of the invention also determines, as at 222, whether or notthe input field into which language is being entered is a “special”input field. In this regard, a special input field is one to whichparticular stored data can be of particular relevance, and suchparticular stored data and is therefore sought to be obtained firstbefore obtaining other data. In effect, therefore, the method can, forinstance, provide proposed output results that are particularly suitedto the input field. As such, the output results are more likely to bethe results desired by the user than otherwise might be the case if allof the data sources were searched in the usual fashion to provideproposed disambiguation results. If the input field is determined by themethod to be special, a special flag is set and processing istransferred, as at 226, for further processing, as at 604 in FIG. 6A, aswill be discussed in greater detail below.

If, however, the input field is determined as at 222 to not be special,processing continues at 224. For each generated prefix object, thememory 20 is consulted, as at 224, to identify, if possible, for eachprefix object one of the word objects 108 in the memory 20 thatcorresponds with the prefix object, meaning that the sequence of lettersrepresented by the prefix object would be either a prefix of theidentified word object 108 or would be substantially identical to theentirety of the word object 108. Further in this regard, the word object108 that is sought to be identified is the highest frequency word object108. That is, the disambiguation function seeks to identify the wordobject 108 that corresponds with the prefix object and that also isassociated with a frequency object 104 having a relatively higherfrequency value than any of the other frequency objects 104 associatedwith the other word objects 108 that correspond with the prefix object.

It is noted in this regard that the word objects 108 in the generic wordlist 88 are generally organized in data tables that correspond with thefirst two letters of various words. For instance, the data tableassociated with the prefix “CO” would include all of the words such as“CODE”, “COIN”, “COMMUNICATION”, and the like. Depending upon thequantity of word objects 108 within any given data table, the data tablemay additionally include sub-data tables within which word objects 108are organized by prefixes that are three linguistic elements or more inlength. Continuing onward with the foregoing example, if the “CO” datatable included, for instance, more than 256 word objects 108, the “CO”data table would additionally include one or more sub-data tables ofword objects 108 corresponding with the most frequently appearingthree-letter prefixes. By way of example, therefore, the “CO” data tablemay also include a “COM” sub-data table and a “CON” sub-data table. If asub-data table includes more than the predetermined number of wordobjects 108, for example a quantity of 256, the sub-data table mayinclude further sub-data tables, such as might be organized according toa four letter prefixes. It is noted that the aforementioned quantity of256 of the word objects 108 corresponds with the greatest numericalvalue that can be stored within one byte of the memory 20.

Accordingly, when, at 224, each prefix object is sought to be used toidentify a corresponding word object 108, and for instance the instantprefix object is “AP”, the “AP” data table will be consulted. Since allof the word objects 108 in the “AP” data table will correspond with theprefix object “AP”, the word object 108 in the “AP” data table withwhich is associated a frequency object 104 having a frequency valuerelatively higher than any of the other frequency objects 104 in the“AP” data table is identified. The identified word object 108 and theassociated frequency object 104 are then stored in a result registerthat serves as a result of the various comparisons of the generatedprefix objects with the contents of the memory 20.

It is noted that one or more, or possibly all, of the prefix objectswill be prefix objects for which a corresponding word object 108 is notidentified in the memory 20. Such prefix objects are considered to beorphan prefix objects and are separately stored or are otherwiseretained for possible future use. In this regard, it is noted that manyor all of the prefix objects can become orphan object if, for instance,the user is trying to enter a new word or, for example, if the user hasmis-keyed and no word corresponds with the mis-keyed input.

Once the result has been obtained at 224, the disambiguation functiondetermines, as at 228, whether artificial variants should be generated.In order to determine the need for artificial variants, the process at228 branches, as at 230, to the artificial variant process depictedgenerally in FIG. 4 and beginning with the numeral 304. Thedisambiguation function then determines, as at 308, whether any of theprefix objects in the result correspond with what had been the defaultoutput 76 prior to detection of the current key input. If a prefixobject in the result corresponds with the previous default output, thismeans that the current input sequence corresponds with a word object 108and, necessarily, the previous default output also corresponded with aword object 108 during the previous disambiguation cycle within thecurrent session.

The next point of analysis is to determine, as at 310, whether theprevious default output was made the default output because of aselection input, such as would have causes the setting of a flag, suchas at 254 of FIG. 3 b, discussed in greater detail below. In the eventthat the previous default output was not the result of a selectioninput, no artificial variants are needed, and the process returns, as at312, to the main process at 232. However, if it is determined at 310that the previous default output was the result of a selection input,then artificial variants are generated, as at 316.

More specifically, each of the artificial variants generated at 316include the previous default output plus one of the linguistic elements48 assigned to the key 28 of the current input. As such, if the key 28of the current input has two linguistic elements, i.e., a firstlinguistic element 52 and a second linguistic element 56, two artificialvariants will be generated at 316. One of the artificial variants willinclude the previous default output plus the first linguistic element52. The other artificial variant will include the previous defaultoutput plus the second linguistic element 56.

However, if it is determined at 308 that none of the prefix objects inthe result correspond with the previous default output, it is nextnecessary to determine, as at 314, whether the previous default outputhad corresponded with a word object 108 during the previousdisambiguation cycle within the current session. If the answer to theinquiry at 314 is no, it is still necessary to determine, as at 318,whether the previous default output was made the default output becauseof a selection input, such as would have causes the setting of the flag.In the event that the previous default output was not the result of aselection input, no artificial variants are needed, and the processreturns, as at 312, to the main process at 232. However, if it isdetermined at 318 that the previous default output was the result of aselection input, then artificial variants are generated, as at 316.

On the other hand, if it is determined that the answer to the inquiry at314 is yes, meaning that the previous default output had correspondedwith a word object, but with the current input the previous defaultoutput combined with the current input has ceased to correspond with anyword object 108, then artificial variants are generated, again as at316.

After the artificial variants are generated at 316, the method thendetermines, as at 320, whether the result includes any prefix objects atall. If not, processing returns, as at 312, to the main process at 232.However, if it is determined at 320 that the result includes at least afirst prefix object, meaning that the current input sequence correspondswith a word object 108, processing is transferred to 324 where anadditional artificial variant is created. Specifically, the prefixobject of the result with which is associated the frequency object 104having the relatively highest frequency value among the other frequencyobjects 104 in the result is identified, and the artificial variant iscreated by deleting the final linguistic element from the identifiedprefix object and replacing it with an opposite linguistic element 48 onthe same key 28 of the current input that generated the final linguisticelement 48 of the identified prefix object. In the event that thespecific key 28 has more than two linguistic elements 48 assignedthereto, the specific key 28 will be considered to have a plurality ofopposite linguistic elements 48. Moreover, each such opposite linguisticelement 48 will be used to generate an additional artificial variant.

Once the need for artificial variants has been identified, as at 228,and such artificial variants have been generated, as in FIG. 4 and asdescribed above, processing continues, as at 232, where duplicate wordobjects 108 associated with relatively lower frequency values aredeleted from the result. Such a duplicate word object 108 could begenerated, for instance, by the frequency learning database 96, as willbe set forth in greater detail below. If a word object 108 in the resultmatches one of the artificial variants, the word object 108 and itsassociated frequency object 104 generally will be removed from theresult because the artificial variant will be assigned a preferredstatus in the output 64, likely in a position preferred to any wordobject 108 that might have been identified.

Once the duplicate word objects 108 and the associated frequency objects104 have been removed at 232, the remaining prefix objects are arranged,as at 236, in an output set in decreasing order of frequency value. Theorphan prefix objects mentioned above may also be added to the outputset, albeit at positions of relatively lower frequency value than anyprefix object for which a corresponding word object 108 was found. It isalso necessary to ensure that the artificial variants, if they have beencreated, are placed at a preferred position in the output set. It isunderstood that artificial variants may, but need not necessarily be,given a position of preference, i.e., assigned a relatively higherpriority or frequency, than prefix objects of the result.

If it is determined, as at 240, that the flag has been set, meaning thata user has made a selection input, either through an express selectioninput or through an alternation input of a movement input, then thedefault output 76 is considered to be “locked,” meaning that theselected variant will be the default prefix until the end of thesession. If it is determined at 240 that the flag has been set, theprocessing will proceed to 244 where the contents of the output set willbe altered, if needed, to provide as the default output 76 an outputthat includes the selected prefix object, whether it corresponds with aword object 108 or is an artificial variant. In this regard, it isunderstood that the flag can be set additional times during a session,in which case the selected prefix associated with resetting of the flagthereafter becomes the “locked” default output 76 until the end of thesession or until another selection input is detected.

Processing then continues, as at 248, to an output step after which anoutput 64 is generated as described above. More specifically, processingproceeds, as at 250, to the subsystem depicted generally in FIG. 6 anddescribed below. Processing thereafter continues at 204 where additionalinput is detected. On the other hand, if it is determined at 240 thatthe flag had not been set, then processing goes directly to 248 withoutthe alteration of the contents of the output set at 244.

The handheld electronic device 4 may be configured such that any orphanprefix object that is included in an output 64 but that is not selectedwith the next input is suspended. This may be limited to orphan prefixobjects appearing in the variant portion 80 or may apply to orphanprefix objects anywhere in the output 64. The handheld electronic device4 may also be configured to similarly suspend artificial variants insimilar circumstances. A reason for such suspension is that each suchorphan prefix object and/or artificial variant, as appropriate, mayspawn a quantity of offspring orphan prefix objects equal to thequantity of linguistic elements 48 on a key 28 of the next input. Thatis, each offspring will include the parent orphan prefix object orartificial variant plus one of the linguistic elements 48 of the key 28of the next input. Since orphan prefix objects and artificial variantssubstantially do not have correspondence with a word object 108, spawnedoffspring objects from parent orphan prefix objects and artificialvariants likewise will not have correspondence with a word object 108.Such suspended orphan prefix objects and/or artificial variants may beconsidered to be suspended, as compared with being wholly eliminated,since such suspended orphan prefix objects and/or artificial variantsmay reappear later as parents of a spawned orphan prefix objects and/orartificial variants, as will be explained below.

If the detected input is determined, as at 212, to be an operationalinput, processing then continues to determine the specific nature of theoperational input. For instance, if it is determined, as at 252, thatthe current input is a selection input, processing continues at 254. At254, the word object 108 and the associated frequency object 104 of thedefault portion 76 of the output 64, as well as the word object 108 andthe associated frequency object 104 of the portion of the variant output80 that was selected by the selection input, are stored in a temporarylearning data register. Additionally, the flag is set. Processing thenreturns to detection of additional inputs as at 204.

If it is determined, as at 260, that the input is a delimiter input,processing continues at 264 where the current session is terminated andprocessing is transferred, as at 266, to the learning functionsubsystem, as at 404 of FIG. 5 a. A delimiter input would include, forexample, the actuation of a <SPACE> key 116, which would both enter adelimiter symbol and would add a space at the end of the word, actuationof the <ENTER> key 44, which might similarly enter a delimiter input andenter a space, and by a translation of the thumbwheel 32, such as isindicated by the arrow 38, which might enter a delimiter input withoutadditionally entering a space.

It is first determined, as at 408, whether the default output at thetime of the detection of the delimiter input at 260 matches a wordobject 108 in the memory 20. If it does not, this means that the defaultoutput is a user-created output that should be added to the new wordsdatabase 92 for future use. In such a circumstance processing thenproceeds to 412 where the default output is stored in the new wordsdatabase 92 as a new word object 108. Additionally, a frequency object104 is stored in the new words database 92 and is associated with theaforementioned new word object 108. The new frequency object 104 isgiven a relatively high frequency value, typically within the upperone-fourth or one-third of a predetermined range of possible frequencyvalues.

In this regard, frequency objects 104 are given an absolute frequencyvalue generally in the range of zero to 65,535. The maximum valuerepresents the largest number that can be stored within two bytes of thememory 20. The new frequency object 104 that is stored in the new wordsdatabase 92 is assigned an absolute frequency value within the upperone-fourth or one-third of this range, particularly since the new wordwas used by a user and is likely to be used again.

With further regard to frequency object 104, it is noted that within agiven data table, such as the “CO” data table mentioned above, theabsolute frequency value is stored only for the frequency object 104having the highest frequency value within the data table. All of theother frequency objects 104 in the same data table have frequency valuesstored as percentage values normalized to the aforementioned maximumabsolute frequency value. That is, after identification of the frequencyobject 104 having the highest frequency value within a given data table,all of the other frequency objects 104 in the same data table areassigned a percentage of the absolute maximum value, which representsthe ratio of the relatively smaller absolute frequency value of aparticular frequency object 104 to the absolute frequency value of theaforementioned highest value frequency object 104. Advantageously, suchpercentage values can be stored within a single byte of memory, thussaving storage space within the handheld electronic device 4.

Upon creation of the new word object 108 and the new frequency object104, and storage thereof within the new words database 92, processing istransferred to 420 where the learning process is terminated. Processingis then returned to the main process, as at 204.

If at 408 it is determined that the word object 108 in the defaultoutput 76 matches a word object 108 within the memory 20, processingthen continues at 416 where it is determined whether the aforementionedflag has been set, such as occurs upon the detection of a selectioninput, and alternation input, or a movement input, by way of example. Ifit turns out that the flag has not been set, this means that the userhas not expressed a preference for a variant prefix object over adefault prefix object, and no need for frequency learning has arisen. Insuch a circumstance, processing continues at 420 where the learningprocess is terminated. Processing then returns to the main process at254.

However, if it is determined at 416 that the flag has been set, theprocessor 20 retrieves from the temporary learning data register themost recently saved default and variant word objects 108, along withtheir associated frequency objects 104. It is then determined, as at428, whether the default and variant word objects 108 had previouslybeen subject of a frequency learning operation. This might bedetermined, for instance, by determining whether the variant word object108 and the associated frequency object 104 were obtained from thefrequency learning database 96. If the default and variant word objects108 had not previously been the subject of a frequency learningoperation, processing continues, as at 432, where the variant wordobject 108 is stored in the frequency learning database 96, and arevised frequency object 104 is generated having a frequency valuegreater than that of the frequency object 104 that previously had beenassociated with the variant word object 108. In the present exemplarycircumstance, i.e., where the default word object 108 and the variantword object 108 are experiencing their first frequency learningoperation, the revised frequency object 104 may, for instance, be givena frequency value equal to the sum of the frequency value of thefrequency object 104 previously associated with the variant word object108 plus one-half the difference between the frequency value of thefrequency object 104 associated with the default word object 108 and thefrequency value of the frequency object 104 previously associated withthe variant word object 108. Upon storing the variant word object 108and the revised frequency object 104 in the frequency learning database96, processing continues at 420 where the learning process is terminatedand processing returns to the main process, as at 254.

If it is determined at 428 that that default word object 108 and thevariant word object 108 had previously been the subject of a frequencylearning operation, processing continues to 436 where the revisedfrequency value 104 is instead given a frequency value higher than thefrequency value of the frequency object 104 associated with the defaultword object 108. After storage of the variant word object 108 and therevised frequency object 104 in the frequency learning database 96,processing continues to 420 where the learning process is terminated,and processing then returns to the main process, as at 254.

With further regard to the learning function, it is noted that thelearning function additionally detects whether both the default wordobject 108 and the variant word object 104 were obtained from thefrequency learning database 96. In this regard, when word objects 108are identified, as at 224, for correspondence with generated prefixobjects, all of the data sources in the memory are polled for suchcorresponding word objects 108 and corresponding frequency objects 104.Since the frequency learning database 96 stores word objects 108 thatalso are stored either in the generic word list 88 or the new wordsdatabase 96, the word object 108 and the associated frequency object 104that are obtained from the frequency learning database 96 typically areduplicates of word objects 108 that have already been obtained from thegeneric word list 88 or the new words database 96. However, theassociated frequency object 104 obtained from the frequency learningdatabase 96 typically has a frequency value that is of a greatermagnitude than that of the associated frequency object 104 that had beenobtained from the generic word list 88. This reflects the nature of thefrequency learning database 96 as imparting to a frequently used wordobject 108 a relatively greater frequency value than it otherwise wouldhave in the generic word list 88.

It thus can be seen that the learning function indicated in FIGS. 5 aand 5 b and described above is generally not initiated until a delimiterinput is detected, meaning that learning occurs only once for eachsession. Additionally, if the final default output is not a user-definednew word, the word objects 108 that are the subject of the frequencylearning function are the word objects 108 which were associated withthe default output 76 and the selected variant output 80 at the timewhen the selection occurred, rather than necessarily being related tothe object that ultimately resulted as the default output at the end ofthe session. Also, if numerous learnable events occurred during a singlesession, the frequency learning function operates only on the wordobjects 108 that were associated with the final learnable event, i.e., aselection event, an alternation event, or a movement event, prior totermination of the current session.

With further regard to the identification of various word objects 108for correspondence with generated prefix objects, it is noted that thememory 22 can include a number of additional data sources 99 in additionto the generic word list 88, the new words database 92, and thefrequency learning database 96, all of which can be consideredlinguistic sources. An exemplary two other data sources 99 are depictedin FIG. 2 a, it being understood that the memory 22 might include anynumber of other data sources 99. The other data sources 99 mightinclude, for example, an address database, a speed-text database, or anyother data source without limitation. An exemplary speed-text databasemight include, for example, sets of words or expressions or other datathat are each associated with, for example, a linguistic element stringthat may be abbreviated. For example, a speed-text database mightassociate the string “br” with the set of words “Best Regards”, with theintention that a user can type the string “br” and receive the output“Best Regards”.

In seeking to identify word objects 108 that correspond with a givenprefix object, the handheld electronic device 4 may poll all of the datasources in the memory 22. For instance the handheld electronic device 4may poll the generic word list 88, the new words database 92, thefrequency learning database 96, and the other data sources 99 toidentify word objects 108 that correspond with the prefix object. Thecontents of the other data sources 99 may be treated as word objects108, and the processor 20 may generate frequency objects 104 that willbe associated such word objects 108 and to which may be assigned afrequency value in, for example, the upper one-third or one-fourth ofthe aforementioned frequency range. Assuming that the assigned frequencyvalue is sufficiently high, the string “br”, for example, wouldtypically be output to the display 60. If a delimiter input is detectedwith respect to the portion of the output having the association withthe word object 108 in the speed-text database, for instance “br”, theuser would receive the output “Best Regards”, it being understood thatthe user might also have entered a selection input as to the exemplarystring “br”.

The contents of any of the other data sources 99 may be treated as wordobjects 108 and may be associated with generated frequency objects 104having the assigned frequency value in the aforementioned upper portionof the frequency range. After such word objects 108 are identified, thenew word learning function can, if appropriate, act upon such wordobjects 108 in the fashion set forth above.

Again regarding FIG. 3 a, when processing proceeds to the filtrationstep, as at 232, and the duplicate word objects 108 and the associatedfrequency objects 104 having relatively lower frequency values arefiltered, the remaining results may include a variant word object 108and a default word object 108, both of which were obtained from thefrequency learning database 96. In such a situation, it can beenvisioned that if a user repetitively and alternately uses one wordthen the other word, over time the frequency objects 104 associated withsuch words will increase well beyond the aforementioned maximum absolutefrequency value for a frequency object 104. Accordingly, if it isdetermined that both the default word object 108 and the variant wordobject 108 in the learning function were obtained from the frequencylearning database 96, instead of storing the variant word object 108 inthe frequency learning database 96 and associating it with a frequencyobject 104 having a relatively increased frequency value, instead thelearning function stores the default word object 108 and associates itwith a revised frequency object 104 having a frequency value that isrelatively lower than that of the frequency object 104 that isassociated with the variant word object 108. Such a schemeadvantageously avoids excessive and unnecessary increases in frequencyvalue.

If it is determined, such as at 268, that the current input is amovement input, such as would be employed when a user is seeking to editan object, either a completed word or a prefix object within the currentsession, the caret 84 is moved, as at 272, to the desired location, andthe flag is set, as at 276. Processing then returns to where additionalinputs can be detected, as at 204.

In this regard, it is understood that various types of movement inputscan be detected from the input device 8. For instance, a rotation of thethumbwheel 32, such as is indicated by the arrow 34 of FIG. 1, couldprovide a movement input, as could the actuation of the <NEXT> key 40,or other such input, potentially in combination with other devices inthe input apparatus 8. In the instance where such a movement input isdetected, such as in the circumstance of an editing input, the movementinput is additionally detected as a selection input. Accordingly, and asis the case with a selection input such as is detected at 252, theselected variant is effectively locked with respect to the defaultportion 76 of the output 64. Any default output 76 during the samesession will necessarily include the previously selected variant.

In the context of editing, however, the particular displayed object thatis being edited is effectively locked except as to the linguisticelement that is being edited. In this regard, therefore, the otherlinguistic elements of the object being edited, i.e., the linguisticelements that are not being edited, are maintained and are employed as acontext for identifying additional word objects 108 and the like thatcorrespond with the object being edited. Were this not the case, a userseeking to edit a letter in the middle of a word otherwise likely wouldsee as a new output 64 numerous objects that bear little or noresemblance to the linguistic elements of the object being edited since,in the absence of maintaining such context, an entirely new set ofprefix objects including all of the permutations of the linguisticelements of the various keystrokes of the object being edited would havebeen generated. New word objects 108 would have been identified ascorresponding with the new prefix objects, all of which couldsignificantly change the output 64 merely upon the editing of a singlelinguistic element. By maintaining the other linguistic elementscurrently in the object being edited, and employing such otherlinguistic elements as context information, the user can much moreeasily edit a word that is depicted on the display 60. As will bedescribed below, however, other types of editing can be employed by theuser, and different rules regarding locking of portions of prefixobjects can be applied in such situations.

In the present exemplary embodiment of the handheld electronic device 4,if it is determined, as at 252, that the input is not a selection input,and it is determined, as at 260, that the input is not a delimiterinput, and it is further determined, as at 268, that the input is not amovement input, in the current exemplary embodiment of the handheldelectronic device 4 the only remaining operational input generally is adetection of the <DELETE> key 86 of the keys 28 of the keypad 24. Upondetection of the <DELETE> key 86, the final linguistic element of thedefault output is deleted, as at 280. At this point, the processinggenerally waits until another input is detected, as at 284. It is thendetermined, as at 288, whether the new input detected at 284 is the sameas the most recent input that was related to the final linguisticelement that had just been deleted at 280. If so, the default output 76is the same as the previous default output, except that the lastlinguistic element is the opposite linguistic element of the keyactuation that generated the last linguistic element. Processing thencontinues to 292 where learning data, i.e., the word object 108 and theassociate frequency object 104 associated with the previous defaultoutput 76, as well as the word object 108 and the associate frequencyobject 104 associated with the new default output 76, are stored in thetemporary learning data register and the flag is set. Such a keysequence, i.e., an input, the <DELETE> key 86, and the same input asbefore, is an alternation input. Such an alternation input replaces thedefault final linguistic element with an opposite final linguisticelement of the key 28 which generated the final linguistic element 48 ofthe default output 76. The alternation input is treated as a selectioninput for purposes of locking the default output 76 for the currentsession, and also triggers the flag which will initiate the learningfunction upon detection of a delimiter input at 260.

If it turns out, however, that the system detects at 288 that the newinput detected at 284 is different than the input immediately prior todetection of the <DELETE> key 86, processing continues at 212 where theinput is determined to be either an operational input or an input of akey having one or more linguistic elements 48, and processing continuesthereafter.

It is also noted that when the main process reaches the output stage at248, an additional process is initiated which determines whether thevariant component 72 of the output 64 should be initiated. Processing ofthe additional function is initiated from 248 at element 504 of FIG. 6.Initially, the method at 508 outputs the text component 68 of the output64 to the display 60. Further processing determines whether or not thevariant component 72 should be displayed.

Specifically, it is determined, as at 512, whether the variant component72 has already been displayed during the current session. If the variantcomponent 72 has already been displayed, processing continues at 516where the new variant component 72 resulting from the currentdisambiguation cycle within the current session is displayed. Processingthen returns to a termination point at 520, after which processingreturns to the main process at 204. If, however, it is determined at 512that the variant component 72 has not yet been displayed during thecurrent session, processing continues, as at 524, to determine whetherthe elapsed time between the current input and the immediately previousinput is longer than a predetermined duration. If it is longer, thenprocessing continues at 516 where the variant component 72 is displayedand processing returns, through 520, to the main process, as at 204.However, if it is determined at 524 that the elapsed time between thecurrent input and the immediately previous input is less than thepredetermined duration, the variant component 72 is not displayed, andprocessing returns to the termination point at 520, after whichprocessing returns to the main process, as at 204.

Advantageously, therefore, if a user is entering keystrokes relativelyquickly, the variant component 72 will not be output to the display 60,where it otherwise would likely create a visual distraction to a userseeking to enter keystrokes quickly. If at any time during a givensession the variant component 72 is output to the display 60, such as ifthe time between successive inputs exceeds the predetermined duration,the variant component 72 will continue to be displayed throughout thatsession. However, upon the initiation of a new session, the variantcomponent 72 will be withheld from the display if the user consistentlyis entering keystrokes relatively quickly.

As mentioned above, in certain circumstances certain data sources can besearched prior to other data sources if the input field is determined,as at 222, to be special. For instance, if the input field is to have aparticular type of data input therein, and this particular type of datacan be identified and obtained, the disambiguated results will be of agreater degree of relevance to the field and have a higher degree ofcorrespondence with the intent of the user. For instance, a physician'sprescription pad typically includes blank spaces into which areinserted, for instance, a patient's name, a drug name, and instructionsfor administering the drug. The physician's prescription pad potentiallycould be automated as an application on the device 4. During entry ofthe patient's name, the data source 99 that would most desirably besearched first would be, for instance, a data source 99 listing thenames and, for instance, the contact information for the doctor'spatients. Similarly, during entry of the drug name, the data source 99that would most desirably be searched first would be the data source 99listing, for instance, names of drugs. By searching these special datasources first, the relevance of the proposed disambiguated results ishigher since the results are more likely to be what is intended by theuser. If the method obtains an insufficient quantity of results in sucha fashion, however, additional results can be obtained in the usualfashion from the other data sources.

As can be seen in FIG. 6A, after processing is transferred to 604 fromthe main process, the method searches, as at 608, for word objects 108and frequency objects 104 in whatever data source 99 is determined tocorrespond with or have some relevance to the special input field. Theinput field typically will inform the operating system of the device 4that it typically receives a particular type of input, and the operatingsystem will determine which data source 99 will be searched first inseeking disambiguation results.

The disambiguation results obtained from the special, i.e.,predetermined, data source 99 are then filtered, as at 612, to eliminateduplicate results, and the quantity of remaining results are thencounted, as at 616, to determine whether the quantity is less than apredetermined number. If the answer to this inquiry is “no”, meaningthat a sufficient quantity of results were obtained from the particulardata source 99, processing is transferred, as at 620, to the mainprocess at 236.

On the other hand, if it is determined at 616 that insufficientdisambiguation results were obtained from the predetermined data source99, addition results typically will desirably be obtained. For instance,in such a circumstance processing continues, as at 624, to processing atwhich the prefix results are arranged in order of decreasing frequencyvalue into a special output set. A special flag is set, as at 628, thatindicates to the method that the additional disambiguation results thatare about to be obtained from the other data sources of the device 4 areto appended to the end of the special output set. Processing istransferred, as at 630, back to the main process at 224, after whichadditional disambiguation results will be sought from the other datasources on the device 4. With the special flag being set, as at 628, theresults that were obtained from the predetermined data source are to belisted ahead of the additional results obtained from the remaining datasources, even if the additional results are associated with relativelyhigher frequency values than some of the results from the predetermineddata source. The method could, however, be applied in different fashionswithout departing from the concept of the invention.

An exemplary input sequence is depicted in FIGS. 1 and 7-11. In thisexample, the user is attempting to enter the word “APPLOADER”, and thisword presently is not stored in the memory 20. In FIG. 1 the user hasalready typed the “AS” key 28. Since the data tables in the memory 20are organized according to two-letter prefixes, the contents of theoutput 64 upon the first keystroke are obtained from the N-gram objects112 within the memory. The first keystroke “AS” corresponds with a firstN-gram object 112 “S” and an associated frequency object 104, as well asanother N-gram object 112 “A” and an associated frequency object 104.While the frequency object 104 associated with “S” has a frequency valuegreater than that of the frequency object 104 associated with “A”, it isnoted that “A” is itself a complete word. A complete word is alwaysprovided as the default output 76 in favor of other prefix objects thatdo not match complete words, regardless of associated frequency value.As such, in FIG. 1, the default portion 76 of the output 64 is “A”.

In FIG. 7, the user has additionally entered the “OP” key 28. Thevariants are depicted in FIG. 7. Since the prefix object “SO” is also aword, it is provided as the default output 76. In FIG. 8, the user hasagain entered the “OP” key 28 and has also entered the “L” key 28. It isnoted that the exemplary “L” key 28 depicted herein includes only thesingle linguistic element 48 “L”.

It is assumed in the instant example that no operational inputs havethus far been detected. The default output 76 is “APPL”, such as wouldcorrespond with the word “APPLE”. The prefix “APPL” is depicted both inthe text component 68, as well as in the default portion 76 of thevariant component 72. Variant prefix objects in the variant portion 80include “APOL”, such as would correspond with the word “APOLOGIZE”, andthe prefix “SPOL”, such as would correspond with the word “SPOLIATION”.

It is particularly noted that the additional variants “AOOL”, “AOPL”,“SOPL”, and “SOOL” are also depicted as variants 80 in the variantcomponent 72. Since no word object 108 corresponds with these prefixobjects, the prefix objects are considered to be orphan prefix objectsfor which a corresponding word object 108 was not identified. In thisregard, it may be desirable for the variant component 72 to include aspecific quantity of entries, and in the case of the instant exemplaryembodiment the quantity is seven entries. Upon obtaining the result at224, if the quantity of prefix objects in the result is fewer than thepredetermined quantity, the disambiguation function will seek to provideadditional outputs until the predetermined number of outputs areprovided. In the absence of artificial variants having been created, theadditional variant entries are provided by orphan prefix objects. It isnoted, however, that if artificial variants had been generated, theylikely would have occupied a place of preference in favor of such orphanprefix objects, and possibly also in favor of the prefix objects of theresult.

It is further noted that such orphan prefix objects may actually beoffspring orphan prefix objects from suspended parent orphan prefixobjects and/or artificial variants. Such offspring orphan prefix objectscan be again output depending upon frequency ranking as explained below,or as otherwise ranked.

The orphan prefix objects are ranked in order of descending frequencywith the use of the N-gram objects 112 and the associated frequencyobjects 104. Since the orphan prefix objects do not have a correspondingword object 108 with an associated frequency object 104, the frequencyobjects 104 associated with the various N-gram objects 112 must beemployed as a fallback.

Using the N-gram objects 112, the disambiguation function first seeks todetermine if any N-gram object 112 having, for instance, threelinguistic elements is a match for, for instance, a final threelinguistic elements of any orphan prefix object. The example of threelinguistic elements is given since the exemplary embodiment of thehandheld electronic device 4 includes N-gram objects 112 that are anexemplary maximum of the three linguistic elements in length, but it isunderstood that if the memory 22 included N-gram objects four linguisticelements in length or longer, the disambiguation function typicallywould first seek to determine whether an N-gram object having thegreatest length in the memory 22 matches the same quantity of linguisticelements at the end of an orphan prefix object.

If only one prefix object corresponds in such a fashion to a threelinguistic element N-gram object 112, such orphan prefix object islisted first among the various orphan prefix objects in the variantoutput 80. If additional orphan prefix objects are matched to N-gramobjects 112 having three linguistic elements, then the frequency objects104 associated with such identified N-gram objects 112 are analyzed, andthe matched orphan prefix objects are ranked amongst themselves in orderof decreasing frequency.

If it is determined that a match cannot be obtained with an N-gramobject 112 having three linguistic elements, then two-linguistic elementN-gram objects 112 are employed. Since the memory 20 includes allpermutations of two-linguistic element N-gram objects 112, a last twolinguistic elements of each orphan prefix object can be matched to acorresponding two-linguistic element N-gram object 112. After suchmatches are achieved, the frequency objects 104 associated with suchidentified N-gram objects 112 are analyzed, and the orphan prefixobjects are ranked amongst themselves in descending order of frequencyvalue of the frequency objects 104 that were associated with theidentified N-gram objects 112. It is further noted that artificialvariants can similarly be rank ordered amongst themselves using theN-gram objects 112 and the associated frequency objects 104.

In FIG. 9 the user has additionally entered the “OP” key 28. In thiscircumstance, and as can be seen in FIG. 9, the default portion 76 ofthe output 64 has become the prefix object “APOLO” such as wouldcorrespond with the word “APOLOGIZE”, whereas immediately prior to thecurrent input the default portion 76 of the output 64 of FIG. 8 was“APPL” such as would correspond with the word “APPLE.” Again, assumingthat no operational inputs had been detected, the default prefix objectin FIG. 9 does not correspond with the previous default prefix object ofFIG. 8. As such, the first artificial variant “APOLP” is generated andin the current example is given a preferred position. The aforementionedartificial variant “APOLP” is generated by deleting the final linguisticelement of the default prefix object “APOLO” and by supplying in itsplace an opposite linguistic element 48 of the key 28 which generatedthe final linguistic element of the default portion 76 of the output 64,which in the current example of FIG. 9 is “P”, so that theaforementioned artificial variants is “APOLP”.

Furthermore, since the previous default output “APPL” corresponded witha word object 108, such as the word object 108 corresponding with theword “APPLE”, and since with the addition of the current input theprevious default output “APPL” no longer corresponds with a word object108, two additional artificial variants are generated. One artificialvariant is “APPLP” and the other artificial variant is “APPLO”, andthese correspond with the previous default output “APPL” plus thelinguistic elements 48 of the key 28 that was actuated to generate thecurrent input. These artificial variants are similarly output as part ofthe variant portion 80 of the output 64.

As can be seen in FIG. 9, the default portion 76 of the output 64“APOLO” no longer seems to match what would be needed as a prefix for“APPLOADER”, and the user likely anticipates that the desired word“APPLOADER” is not already stored in the memory 20. As such, the userprovides a selection input, such as by scrolling with the thumbwheel 32,or by actuating the <NEXT> key 40, until the variant string “APPLO” ishighlighted. The user then continues typing and enters the “AS” key.

The output 64 of such action is depicted in FIG. 10. Here, the string“APPLOA” is the default portion 76 of the output 64. Since the variantstring “APPLO” became the default portion 76 of the output 64 (notexpressly depicted herein) as a result of the selection input as to thevariant string “APPLO”, and since the variant string “APPLO” does notcorrespond with a word object 108, the linguistic element strings“APPLOA” and “APPLOS” were created as an artificial variants.Additionally, since the previous default of FIG. 9, “APOLO” previouslyhad corresponded with a word object 108, but now is no longer incorrespondence with the default portion 76 of the output 64 of FIG. 10,the additional artificial variants of “APOLOA” and “APOLOS” were alsogenerated. Such artificial variants are given a preferred position infavor of the three displayed orphan prefix objects.

Since the current input sequence in the example no longer correspondswith any word object 108, the portions of the method related toattempting to find corresponding word objects 108 are not executed withfurther inputs for the current session. That is, since no word object108 corresponds with the current input sequence, further inputs willlikewise not correspond with any word object 108. Avoiding the search ofthe memory 20 for such nonexistent word objects 108 saves time andavoids wasted processing effort.

As the user continues to type, the user ultimately will successfullyenter the word “APPLOADER” and will enter a delimiter input. Upondetection of the delimiter input after the entry of “APPLOADER”, thelearning function is initiated. Since the word “APPLOADER” does notcorrespond with a word object 108 in the memory 20, a new word object108 corresponding with “APPLOADER” is generated and is stored in the newwords database 92, along with a corresponding new frequency object 104which is given an absolute frequency in the upper, say, one-third orone-fourth of the possible frequency range. In this regard, it is notedthat the new words database 92 and the frequency learning database 96are generally organized in two-linguistic element prefix data tablessimilar to those found in the generic word list 88. As such, the newfrequency object 104 is initially assigned an absolute frequency value,but upon storage the absolute frequency value, if it is not the maximumvalue within that data table, will be changed to include a normalizedfrequency value percentage normalized to whatever is the maximumfrequency value within that data table.

As a subsequent example, in FIG. 11 the user is trying to enter the word“APOLOGIZE”. The user has entered the key sequence “AS” “OP” “OP” “L”“OP”. Since “APPLOADER” has now been added as a word object 108 to thenew words database 92 and has been associated with frequency object 104having a relatively high frequency value, the prefix object “APPLO”which corresponds with “APPLOADER” has been displayed as the defaultportion 76 of the output 64 in favor of the variant prefix object“APOLO”, which corresponds with the desired word “APOLOGIZE.” Since theword “APOLOGIZE” corresponds with a word object 108 that is stored atleast in the generic word list 88, the user can simply continue to enterkeystrokes corresponding with the additional letters “GIZE”, which wouldbe the letters in the word “APOLOGIZE” following the prefix object“APOLO”, in order to obtain the word “APOLOGIZE”. Alternatively, theuser may, upon seeing the output 64 depicted in FIG. 11, enter aselection input to affirmatively select the variant prefix object“APOLO”. In such a circumstance, the learning function will be triggeredupon detection of a delimiter symbol, and the word object 108 that hadcorresponded with the linguistic element string “APOLO” at the time theselection input was made will be stored in the frequency learningdatabase 92 and will be associated with a revised frequency object 104having a relatively higher frequency value that is similarly stored inthe frequency learning database 92.

An additional feature of the handheld electronic device 4 is depictedgenerally in FIG. 12. In some circumstances, it is desirable that thedisambiguation function be disabled. For instance, when it is desired toenter a password, disambiguation typically is relatively more cumbersomethan during ordinary text entry. As such, when the system focus is onthe component corresponding with the password field, the componentindicates to the API that special processing is requested, and the APIdisables the disambiguation function and instead enables, for instance,a multi-tap input interpretation system. Alternatively, other inputinterpretation systems could include a chording system or apress-and-hold/press-and-release interpretation system. As such, whilean input entered with the disambiguation function active is an ambiguousinput, by enabling the alternative interpretation system, such as theexemplary multi-tap system, each input can be largely unambiguous.

As can be understood from FIG. 12, each unambiguous input is displayedfor a very short period of time within the password field 120, and isthen replaced with another output, such as the asterisk. The linguisticelement “R” is shown displayed, it being understood that such display isonly for a very short period of time.

As can be seen in FIGS. 1 and 7-11, the output 64 includes the displayedgraphic 46 near the lower end of the variant component 72, and that thedisplayed graphic 46 is highly similar to the graphic 42 of the <NEXT>key 40. Such a depiction provides an indication to the user which of thekeys 28 of the keypad 24 can be actuated to select a variant output. Thedepiction of the displayed graphic 46 provides an association betweenthe output 64 and the <NEXT> key 40 in the user's mind. Additionally, ifthe user employs the <NEXT> key 40 to provide a selection input, theuser will be able to actuate the <NEXT> key 40 without moving the user'shands away from the position the hands were in with respect to thehousing 6 during text entry, which reduces unnecessary hand motions,such as would be required if a user needed to move a hand to actuate thethumbwheel 32. This saves time and effort.

It is also noted that the system can detect the existence of certainpredefined symbols as being delimiter signals if no word object 108corresponds with the text entry that includes the symbol. For instance,if the user desired to enter the input “one-off”, the user might beginby entering the key sequence “OP” “BN” “ER” “ZX” “OP”, with the “ZX”actuation being intended to refer to the hyphen symbol disposed thereon.Alternatively, instead of typing the “ZX” key the user might actuate an<ALT> entry to unambiguously indicate the hyphen.

Assuming that the memory 20 does not already include a word object 108of “one-off”, the disambiguation function will detect the hyphen asbeing a delimiter input. As such, the key entries preceding thedelimiter input will be delimited from the key entries subsequent to thedelimiter input. As such, the desired input will be searched as twoseparate words, i.e., “ONE” and “OFF”, with the hyphen therebetween.This facilitates processing by more narrowly identifying what is desiredto be searched.

Another type of editing feature is depicted generally in FIGS. 13-17.During text entry, if a user determines that the wrong word is beingentered or output, the user may decide to delete certain of the terminalletters and to reenter the text. For instance, and as is depictedgenerally in FIG. 13, the user has entered the keystrokes “BN” “ER” “UI”“BN” “GH”. For example, the user has sought to enter the word “BRING”.The device 4 has, however, provided as a default component 768A the word“BEING”. It is clear to the user that the second keystroke, i.e., the“ER” keystroke, was not an incorrect keystroke, but rather the devicesimply provided an output other than what was desired by the user. Insuch a circumstance, the user may enter a deletion input, i.e., a numberof actuations of the <DEL> key with respect to the terminal portion ofthe default component 768A, i.e., the terminal letters G, N, I, and E.The initial portion of what had been the default component 768A, i.e.,the letter B depicted with the numeral 768B in FIG. 14, has not beendeleted because it is what the user desired. It is noted that while avariant component 772A, 772B, and 772C have been depicted schematicallyin FIGS. 13-15, the specific contents of such variant components 772A,772B, and 772C has been left out of FIGS. 13-15 for purposes ofsimplicity.

If the user at this point reenters the “ER” key, as is depictedgenerally in FIG. 15, the initial portion of what had been the defaultoutput 768A, i.e., the letter B, becomes “locked”. Moreover, the portionof the default component 768C that results from the actuation of the“ER” key is an opposite character of what had previously been output inthe default component 768A. The letter E had been the output adjacentthe initial portion of the default component 768A, but a reactuation ofthe “ER” key results in the default output now being the letter R.

If the user continues reactuating the same keys sequentially adjacentthe letter that had been the subject of the character flip mentioned inthe previous paragraph, that is, the E being flipped in favor of the R,the flipped character, i.e., R, also becomes locked. However, theportion of the default component 768D that resulted from reactuation ofthe “UI” key is not locked at this point, as can be seen in FIG. 16.Rather, the device provides a variant output 772D that includes thevariants that correspond with the locked letters B and R, plus thevarious letters assigned to the “UI” key. In the example shown, thedevice has provided as a default portion 776D the character string BRI,and has provided as a variant portion 780D the character string BRU.

If at this point the “BN” key is reactuated, as is depicted generally inFIG. 17, the locked letters B and R remain locked, and the device 4provides a variant component 772E that includes the locked letters B andR plus the various letters assigned to the “UI” key and to the “BN” key.In the depicted exemplary circumstance, the default portion 776E, andthus the default component 768E, is the letter string BRIN. Threevariants are provided as the variant portion 780E.

It is noted that if any of the keys actuated after deletion of theterminal portion of the default component 768A is a key other than whathad originally been entered to provide the terminal portion, all lettersin the word being typed become unlocked. It thus can be seen that if theuser notices a word is being output incorrectly, the device 4 provides away in which the error can be corrected. For example, if the userdeletes terminal characters to the point that the erroneous output beganto occur, i.e., the output of the letter E instead of the desired letterI, the letter can be flipped if the same key is reactuated. Ifsubsequent keys are similarly reactuated, the flipped letter becomeslocked, and variants are provided for the subsequent keys since thedevice 4 cannot be certain that the other letters in the terminalportion of the default component 768A were what the user desired. Theuser thus is given the opportunity to choose a variant after thecharacter flip. On the other hand, if the user simply entered anincorrect key, upon actuation of the new key all letters are unlockedand the disambiguation routine operates on the input as if it is a newinput without any locked letters.

An enhanced letter case entry feature is depicted in an exemplaryfashion in FIGS. 18-21. The memory 20 is capable of storing word objectswith specific upper case and lower case letter makeups. For instance,the device 4 may have stored therein the words “blackberry”, whichrefers to a fruit, and the word “BlackBerry”, which is a proper nounhaving two capital letters. The case makeup, i.e., the makeup of upperand lower case elements, of these two words can be said to be different.However, the device advantageously provides capitalization in somecircumstances to obviate the need for the user to always enter, forexample, a shift key to obtain each capital letter desired in theoutput.

In an exemplary circumstance where the words “blackberry” and“BlackBerry”, for instance, are both stored on the device 4, the usercan obtain desired results with relatively reduced effort. For instance,and as is depicted generally in FIG. 18, the user has entered the keys“BN” “L” “AS” “CV” “JK” and “BN”, and only one of the “BN” entries wasentered as upper case. In the present example, it was the second “BN”entry that was upper case. The device 4 compares the case makeup of theinput with the case makeup of the identified word objects in the memory20. Since the case makeup of what the user has entered includes at leastone upper case “BN”, and since the case makeup of at least a portion ofthe word “BlackBerry” matches at least a portion of the case makeup ofthe input, i.e., an upper case “B”, the entire default component 868Aand default portion 876A match the case makeup of the word “BlackBerry”.That is, even though the user entered only one upper case “BN”, thedevice 4 has proposed as a preferred variant the letter string BlackBwith two capital letters since it is automatically providingcapitalization in accordance with what the device 4 believes to be thewishes of the user. In the example presented in FIG. 18, the lower casecharacter string “blackb” is output as a variant portion 880A of thevariant component 872A, although this extra output can be eliminatedwithout departing from the concept of the invention.

In the example depicted generally in FIG. 19, the user has entered thesame character string, but all lower case. Since no upper case entry wasmade by the user, and thus the device 4 has not been apprised of anyinterest the user may have in obtaining a capitalized output, thedefault portion 876B of the variant component 872B, and thus also thedefault component 868B, is the lower case character string “blackb” as apreferred variant. However, the upper case letter string BlackB is alsoprovided as a variant portion 880B to enable to user to obtaincapitalization of, say, two letters, with only a single selection inputwith respect to the variant portion 880B, if desired by the user.

Another example is presented in FIGS. 20 and 21. If a word object isstored in the memory 20 with a case makeup having one or more caseelements that are upper case, and no corresponding lower case wordobject is stored in the memory 20, an input of all lower case actuationsthat corresponds with the upper case word will result in an output ofthe upper case word in accordance with the case makeup thereof. Forinstance, the user may have decided to input the male name “Todd”. InFIG. 20, the user has already actuated the keys “TY” “OP” and “DF” inlower case. Since the user has not provided any upper case input, thedefault portion 867C and the default component 868C are in lower case inthe present example, such as the character string “tod”, which mightcorrespond with the word “today” which is stored in the memory in afashion having a case makeup consisting of lower case letters. Thecharacter string “Tod” having a case makeup that includes a case elementthat is upper case is provided as part of a variant portion 880C of avariant component 872C.

However, if the user provides another lower case input of the “DF” key,the only word object in the memory 20 which corresponds with the inputis the word “Todd”, which has a case makeup that includes a case elementthat is upper case. Since the word “Todd” was, in the present example,the only word element that corresponded with the input, the defaultportion 876D of the variant component 872D, as well as the defaultcomponent 868D, is provided in accordance with the case makeup of theword object “Todd” despite the entry of all lower case input. The device4 thus advantageously provides automated capitalization in certaincircumstances.

An enhanced word frequency learning feature is depicted generally inFIGS. 22-23. In the circumstance where a user is entering a given inputsequence that corresponds with more than one word, such as in the waythe input sequence “AS” “ER” “ER” can correspond with the words “are”and “see”, a user entering this sequence followed by a delimiter inputwill receive as output whichever of the two words “are” and “see” isassociated with the word object having the highest frequency valuedespite the intentions of the user. In the example depicted in FIG. 22,the user has entered this input sequence, and the default component968A, as well as the default portion 976A of the variant component 972A,is the word “are”. If the user “forces” the word “see” by entering aselection input as to the variant portion 980A “see”, as is depictedgenerally in FIG. 23 with respect to the variant component 972B thereof,the default portion 968B becomes “see”. In such a circumstance, if theuser enters a delimiter input, the device 4 outputs the word “see”.

At this point, however, no frequency values have been adjusted on thedevice 4. If the user “forces” a lower frequency word twice in a row,however, the frequency values will be altered on the device 4 to reflectthe user's needs. That is, if the user a second time enters the inputsequence “AS” “ER” “ER” and selects the word “see” in favor of thedefault word “are”, without in the meantime having entered the samesequence and accepted the default “are”, the word object “see” will beassociated with a new frequency object having a relatively higherfrequency value than the frequency value of the frequency object withwhich the word object “are” is associated.

Thereafter, if the user enters the input sequence “AS” “ER” “ER”, thedefault component will be “see” due to the altered frequency value. If,however, the user twice in a row forces the word “are” upon enteringthis key sequence, without an intervening event of accepting the default“see”, the word object “are” will have its frequency value adjusted sothat it will return to being the default word object.

While specific embodiments of the invention have been described indetail, it will be appreciated by those skilled in the art that variousmodifications and alternatives to those details could be developed inlight of the overall teachings of the disclosure. Accordingly, theparticular arrangements disclosed are meant to be illustrative only andnot limiting as to the scope of the invention which is to be given thefull breadth of the claims appended and any and all equivalents thereof.

1. A method of disambiguating an input into a handheld electronicdevice, the handheld electronic device including an input apparatus, anoutput apparatus, and a processor apparatus including a memory having aplurality of objects stored therein, the plurality of objects includinga plurality of language objects, each language object of at least aportion of the plurality of language objects comprising at least a firstlinguistic element, the plurality of language objects including aplurality of word objects the input apparatus including a plurality ofinput members, each of at least a portion of the input members of theplurality of input members having a plurality of linguistic elementsassigned thereto, the method comprising: detecting an ambiguous inputincluding a number of input member actuations of a number of the inputmembers of the plurality of input members, each of at least a portion ofthe input members of the number of input members including a number oflinguistic elements assigned thereto, at least one of the input membersof the number of input members having a plurality of linguistic elementsassigned thereto, wherein the ambiguous input has an input case makeup;generating a number of prefix objects corresponding with the ambiguousinput, each prefix object of the number of prefix objects including anumber of the linguistic elements of the number of the input members ofthe ambiguous input; for at least a first prefix object of the number ofprefix objects, identifying at least a pair of word objects of theplurality of language objects corresponding with the at least a firstprefix object, each of the at least a pair of word objects having thenumber of linguistic elements of the first prefix object set forth inthe same order, at least a portion of a first word object of the atleast a pair of word objects having a first case makeup comprising anumber of case elements, at least a portion of a second word object ofthe at least a pair of word objects having a second case makeupcomprising a number of case elements, the first case makeup and thesecond case makeup being different than one another; determining that atleast a portion of the input case makeup corresponds with at least aportion of the first case makeup; outputting among a predeterminedquantity of alternative proposed interpretations of the ambiguous input,as a relatively more preferred variant, the at least a first prefixobject in accordance with the first case makeup; and outputting as arelatively less preferred variant the at least a first prefix object inaccordance with the second case makeup.
 2. The method of claim 1,further comprising determining that the at least a portion of the inputcase makeup includes a case element that is upper case and the caseelement in the input case makeup that is upper case corresponds to anupper case element in the first case makeup to output as the relativelymore preferred variant the at least a first prefix object in accordancewith the first case makeup.
 3. The method of claim 2, further comprisingdetermining that another portion of the input case makeup includes acase element that is lower case, and determining that a correspondingcase element of the first case makeup is a case element that is uppercase.
 4. The method of claim 1 including the steps of: associating atleast a portion of the number of prefix objects respectively with acorresponding word object having a frequency object with a correspondingfrequency value stored in memory; and outputting the portion of thenumber of prefix objects in a list in descending order of frequencyvalue except that the more preferred variant is listed ahead of therelatively less preferred variant.